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Profile characteristics of temporal stability of soil water storage in two land uses |
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| Authors: | She Dongli Liu Dongdong Liu Yingying Liu Yi Xu Cuilan Qu Xin Chen Fang |
| Institution: | 1. Key Laboratory of Efficient Irrigation-Drainage and Agricultural Soil-Water Environment in Southern China, Ministry of Education, College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China 2. Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China 3. Jiangsu Provincial center for Land Consolidation and Rehabilitation, Nanjing, Jiangsu, 210024, China |
| Abstract: | Information on soil water storage (SWS) within soil profiles is essential in order to characterize hydrological and biological processes. One of the challenges is to develop low cost and efficient sampling strategies for area estimation of profile SWS. To test the existence of certain sample locations which consistently represent mean behavior irrespective of soil profile wetness, temporal stability of SWS in ten soil layers from 0 to 400 cm was analyzed in two land uses (grassland and shrub land), on the Chinese Loess Plateau. Temporal stability analyses were conducted using two methods viz. Spearman rank correlation coefficient (r s) and mean relative differences. The results showed that both spatial variability and time stability of SWS increased with increasing soil depth, and this trend was mainly observed at above 200 cm depth. High r s (p?<?0.01) indicated a strong temporal stability of spatial patterns for all soil layers. Temporal stability increased with increasing soil depth, based on either r s or standard deviation of relative difference index. The boundary between the temporal unstable and stable layer of SWS for shrub land and grassland uses was 280 and 160 cm depth, respectively. No single location could represent the mean SWS for all ten soil layers. For temporal stable layers, however, some sampling locations could represent the mean SWS at different layers. With increasing soil depth, more locations were able to estimate the mean SWS of the area, and the accuracy of prediction for the representative locations also increased. |
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